Using GIS maps for measuring equitable community health and nutrition programs. (20th October 2021)

• Record Type: Journal Article
• Authors: Kim, H; Ackerson, J
• Is Part Of: European journal of public health. Volume 31(2021)Supplement 3
• Publication Date: 2021-10-20
• Subjects: Epidemiology -- Europe -- Periodicals; Public health -- Europe -- Periodicals; 362.109405
• DOI: 10.1093/eurpub/ckab164.206
• Languages: English
• ISSNs: 1101-1262

Abstract

Abstract: Background: The University of Minnesota (UMN) Extension Supplemental Nutrition Assistance Program Education (SNAP-Ed) documents the geographic data of statewide community health and nutrition policy, systems, and environmental change (PSE) programs for low-income communities. SNAP-Ed collaborates with communities to organize food security efforts, offer direct nutrition education, and consult with organizations about promoting healthy foods and physical activities. UMN Extension's SNAP-Ed implemented 972 PSE programs with 1, 077 community partners and reached 624, 129 people between 2017 and 2020. Methods: SNAP-Ed's support of population-level health and nutrition initiatives is intended to increase access to healthy foods for SNAP-Ed eligible individuals. Geospatial analysis can identify if program efforts reach target populations. Low-income and low-food access census tracts were identified by using the U.S Treasury and USDA, respectively. In this study, buffer boundaries were set around SNAP-Ed designated PSE programs, paralleling USDA's access boundaries of 10 miles for rural areas and one mile for urban areas. Low-program access tracts were identified by their weighted population centroid or geographic boundary's intersection with the food security program buffers. Results: Results show that 78.5% of low-food access and low-income areas have moderate to high-program access. Furthermore, moderate to high-program access communities tend to have higher percentages of BIPOC population and higher poverty rates when compared to low-program access communities among low-income and low-food access communities. Conclusions: UMN Extension will continue to use GIS analysis for understanding where to promote, support, and organize around the implementation of food security programs and therefore better reach eligible audiences. Key messages: Using geospatial analysis allows us to measure community health and nutrition PSE program access and program access equity. Minnesota's low-income and low-food access population has higher community health and nutrition programs access.